Github user mengxr commented on the pull request:
https://github.com/apache/spark/pull/3099#issuecomment-62693414
I tried to hide APIs as much as I can while maintaining the code at a level
where user can actually try creating, configuring, and tuning a pipeline. All
major classes are marked as "AlphaComponent". The schema transformation layer
is hidden. `Identifiable` and `UnaryTransformer` are marked `private[ml]`. As a
result, I copied `Tokenizer` to `ml.feature`. Attached is a list of public
classes. @mateiz
~~~
org.apache.spark.ml
Estimator
Evaluator
Model
Pipeline
PipelineModel
PipelineStage
Transformer
org.apache.spark.ml.classification
LogisticRegression
LogisticRegressionModel
org.apache.spark.ml.evaluation
BinaryClassificationEvaluator
org.apache.spark.ml.feature
HashingTF
StandardScaler
StandardScalerModel
Tokenizer
org.apache.spark.ml.param
BooleanParam
DoubleParam
FloatParam
IntParam
LongParam
Param
ParamMap
ParamPair
Params
org.apache.spark.ml.tuning
CrossValidator
CrossValidatorModel
ParamGridBuilder
~~~
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